When a smoothed image obtained by blurring an image is generated in digital image processing, the average value of the level values of pixels within a filter size is conventionally used as the signal level of a pixel of interest by using a low-pass filter. However, when using a low-pass filter, there is a problem in that an edge portion that has a large difference between level values also becomes dim because the average value of the level values of the pixels within a filter size is used as the signal level of a pixel of interest. Specifically, as illustrated in FIG. 7, when using a low-pass filter, a gradient for an edge portion having a large brightness difference in a process target image that is indicated by the solid line gets dull in the case of a low-pass filter image (LPF image in the present drawing) output from the low-pass filter that is indicated by the dotted line, and thus it is impossible to hold the edge portion.
To solve such a problem, various conventional technologies for accurately saving the edge portion of an image and blurring the other portion have been considered. A technology related to a face image processing apparatus (image processing apparatus) that uses an epsilon filter has been known as disclosed in, for example, Japanese Laid-open Patent Publication No. 2000-105815.
Specifically, as illustrated in FIG. 8, the face image processing apparatus uses a pixel located at an image coordinates (m, n) as a pixel of interest and uses surrounding pixels (in this case, eight pixels with the following coordinates relative to the pixel of interest as peripheral pixels: coordinates (m−1, n−1), coordinates (m, n−1), coordinates (m+1, n−1), coordinates (m−1, n), coordinates (m+1, n), coordinates (m−1, n+1), coordinates (m, n+1), and coordinates (m+1, n+1)). Next, the face image processing apparatus computes the difference between the level value (for example, the gradation value of a luminance signal) of the pixel of interest and the level value of each peripheral pixel and extracts a peripheral pixel for which the computed difference is smaller than a predetermined threshold value TH. Then, the face image processing apparatus outputs a value obtained by adding a pixel value, which is obtained by multiplying the signal level of the extracted peripheral pixel by a predetermined coefficient, to the pixel value of the pixel of interest as a pixel value of the pixel of interest.
In this manner, in the conventional technology disclosed in Japanese Laid-open Patent Publication No. 2000-105815, the level width of the gradation value is limited by using only a peripheral pixel for which the difference with the level value of the pixel of interest is smaller than the threshold value TH as a processing target. Therefore, as illustrated in FIG. 9, the gradient of the edge portion of an epsilon filter image (c filter image in the present drawing) output from an epsilon filter that is indicated by the dotted line does not get dull and the gradient of the edge portion of a process target image indicated by the solid line is held. As a result, the edge portion can be accurately saved and the other portion except for the edge portion can be blurred.
In the above-described conventional technology, there are problems in that a noise rejection intensity cannot be easily controlled and in that a noise rejection process cannot be performed at high speed even if the noise rejection intensity can be controlled.
Specifically, noises inside an image include a noise caused by a brightness (luminance) change and a noise caused by a color change. A color change stands out. A noise caused by the color change tends to largely exist in a low-luminance area. Therefore, to remove the noise caused by the color change in such a manner that an input image is not unnatural, it is necessary to change the rejection intensity of the color change noise in accordance with the luminance value of the input image. For example, in the conventional technology that uses the epsilon filter disclosed in Japanese Laid-open Patent Publication No. 2000-105815, it is extremely easy to incorporate a mechanism for changing filter characteristics from brightness component information in the case of noise rejection for a chroma (color) component. However, pixels other than filtering target information in an image are treated as pixel of interests and differences between the level values of the pixel of interests and the level values of peripheral pixels should be computed and compared with a threshold value. Therefore, there is a problem in that the processing load is large and a high-speed process is difficult due to the inclusion of condition branch processes by variables.